Iterative Interval Estimation-Based Fault Detection for Discrete Time T-S Fuzzy Systems

Mouquan Shen, Tu Zhang, Zheng Guang Wu, Qing Guo Wang, Song Zhu

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

This article investigates fault detection (FD) for discrete-time T-S fuzzy systems via an iterative interval estimation method. By means of system output and the iterative estimation of unknown disturbances, two iterative subsystems are employed to establish iterative state reconstruction free of faults. Resorting to a structure separation technique and the $H_{\infty }$ requirement imposed on estimated errors, a sufficient condition is formulated in terms of linear matrix inequality to guarantee the asymptotically stability of the error systems. With the help of the zonotope reachability technique, the state interval without faults consideration is rebuilt in terms of the error boundary. Subsequently, an FD scheme is proposed by checking residual signals whether exceed the residual interval generated from the established error interval. Simulation comparison is provided to verify the validity of the proposed iterative FD scheme.

Original languageEnglish
Pages (from-to)6966-6974
Number of pages9
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume53
Issue number11
DOIs
StatePublished - 1 Nov 2023

Keywords

  • Fault detection (FD)
  • TS fuzzy system
  • interval estimation
  • robust control

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